A Simple Outdoor Environment Obstacle Detection Method Based on Information Fusion of Depth and Infrared

Abstract

In allusion to the existing low recognition rate and robustness problem in obstacle detection; a simple but effective obstacle detection algorithm of information fusion in the depth and infrared is put forward. The scenario is segmented by the mean-shift algorithm and the pixel gradient of foreground is calculated. After pretreatment of edge detection and morphological operation, the depth information and infrared information are fused. The characteristics of depth map and infrared image in edge detection are used for the raised method, the false rate of detection is reduced, and detection precision is improved. Since the depth map and infrared image are not affected by natural sunlight, the influence on obstacle recognition due to the factors such as light intensity and shadow is effectively reduced and the robustness of the algorithm is also improved. Experiments indicate that the detection algorithm of information fusion can accurately identify the small obstacle in the view and the accuracy of obstacle recognition will not be affected by light. Hence, this method has great significance for mobile robot or intelligent vehicles on obstacle detection in outdoor environment.